Tag Archives: proportionality

April 23, 2024 · 10:04 AM

Index-In-Place eDiscovery Tech is in High Demand, but Beware of False Vendor Claims

By John Patzakis

Proportionality-based eDiscovery is a goal that all in-house corporate legal teams want to attain. Under Federal Rule of Civil Procedure 26(b)(1), parties may discover any non-privileged material that is relevant to any party’s claim or defense and proportional to the needs of the case. However, most core eDiscovery costs (outside of attorney review) stem from over-collection of electronically stored information (ESI), and over-collection thwarts the ability to attain proportionality. Law firm Nelson Mullins notes that “over preservation tends to have its own costs relating to storage of large amounts of electronically stored information (ESI) and the resources needed to manage it; leads to increased downstream e-discovery costs associated with collection, processing, and review.”

This is why accurate pre-collection data insight is a game-changing capability that enables counsel to set reasonable discovery limits and ultimately process, host, review and produce much less ESI. Counsel can further use pre-collection proportionality analysis to gather key information, develop a litigation budget, and better manage litigation deadlines. Such insights can also foster cooperation by informing the parties early in the process about where relevant ESI is located, and what keywords and other search parameters can identify and pinpoint relevant ESI.

And the means to enable this capability is distributed index and search in-place technology. Indexing and search in-place in this context means that a software-based indexing technology is deployed directly onto fileservers, laptops, or in the cloud to address cloud-based data sources. This indexing occurs without a bulk transfer of the data to a central location. Once indexed, the searches are performed in a few seconds, with complex Boolean operators, metadata filters and regular expression searches. The searches can be iterated and repeated without limitation, which is critical for large data sets.

However, with this capability being highly valued, many vendors have parroted this messaging, but have offerings that do not qualify as true index-in-place. True distributed index-in-place means that the search indexes are forward-deployed, and are actually installed on the target laptop, Mac computer, fileserver or into the cloud near where the target cloud data sources exist. Transferring data in bulk to a central appliance or server farm via a collector agent or Robocopy function does not qualify. A true index-in-place capability uniquely enables scalability, targeted collection and also minimizes security and data governance risks in eDiscovery and information governance matters.

Conversely, a process requiring massive data copying, migration and centralization does not scale and creates significant data, governance and privacy issues by needlessly duplicating data. For instance, if a matter requires that 10 terabytes be scanned to determine if relevant ESI exists within that data corpus, and the eDiscovery collection platform being used has no index-in-place capability, then all 10 terabytes must be copied and transferred to the tool for indexing and analysis. These limitations stem from tool vendors simply utilizing open source indexing platforms like Lucene or Elastic Search that are not forward-deployable and must reside in centralized locations with a very large amount of computing resources to make them viable for the type of data and data volumes typically seen in discovery and information governance matters.

This is why X1 leverages proprietary and patented index and search technology that is readily forward deployable and thus can scale and allow true distributed indexing in-place. X1 Enterprise Collect significantly streamlines the eDiscovery workflow with integrated culling and deduplication, thereby eliminating the need for expensive and cumbersome ESI processing tools. That way, the ESI can be populated straight into Relativity from an X1 collection without multiple hand offs, extensive project management and inefficient data processing.

The ability to directly and transparently collect data from custodian laptops, desktops, Microsoft 365 and other cloud sources into a RelativityOne/Relativity workspace is a game-changer that enables attorneys to begin review in hours rather than weeks.

For a demonstration of the X1 Enterprise Collect Platform, contact us at sales@x1.com. For more details on this innovative solution, please visit www.x1.com/x1-enterprise-collect-platform.

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May 19, 2020 · 1:14 PM

True Proportionality for eDiscovery Requires Smart Pre-Collection Analysis

By John Patzakis

Proportionality-based eDiscovery is a goal that all judges and corporate attorneys want to attain. Under Federal Rule of Civil Procedure 26(b)(1), parties may  discover any non-privileged material that is relevant to any party’s claim or defense and proportional to the needs of the case. However attorneys representing enterprises are essentially flying blind on this analysis when it matters most. Prior to the custodian data being actually collected, processed and analyzed, attorneys do not have any real visibility into the potentially relevant ESI across an organization. This is especially true in regard to unstructured, distributed data, which is invariably the majority of ESI that is ultimately collected in a given matter.proportionality

If accurate pre-collection data insight were available to counsel, that game-changing factor would enable counsel to set reasonable discovery limits and ultimately process, host, review and produce much less ESI.  Counsel can further use pre-collection proportionality analysis to gather key information, develop a litigation budget, and better manage litigation deadlines. Such insights can also foster cooperation by informing the parties early in the process about where relevant ESI is located, and what keywords and other search parameters can identify and pinpoint relevant ESI.

The problem is any keyword protocols are mostly guesswork at the early stage of litigation, as, under outdated but still widely used eDiscovery practices, the costly and time consuming steps of actual data collection and processing must occur before meaningful proportionality analysis can take place. When you hear eDiscovery practitioners talk about proportionality, they are invariably speaking of a post-collection, pre-review process. But without requisite pre-collection visibility into distributed ESI, counsel typically resort to directing broad collection efforts, resulting in much greater costs, burden and delays.

X1 recently hosted a webinar featuring prominent industry experts including attorney David Horrigan of Relativity, Mandi Ross of Prism Litigation Technology and Ben Sexton of JND eDiscovery, addressing the issues of remote ESI collection and proportionality. David Horrigan outlined in succinct detail the legal concepts of proportionality under the Federal Rules, the Sedona Principles and as applied in case law. Mandi Ross explained how she applies proportionality when advising lawyers and judges through custodian interviews, coupled with detailed keyword search term analysis based upon the matter’s specific claims and defenses. She noted that technology such as X1 greatly enables the application of her practice in real time: “The ability to index in place is a game changer because we have the ability to gain insight into the data and validate custodian interview data without first requiring that data to be collected.”

The webinar also featured a live exercise performing a pre-collection proportionality analysis on remote employee data with X1 Distributed Discovery. The panelists provided comments and insights contrasting what they saw with the outdated, costly, and time consuming process involving manual data collection and subsequent migration into a hardware processing appliance. The later process negates counsel’s ability to conduct any meaningful application of proportionality, without first incurring significant expense and loss of time. A recording of the webinar can be accessed here.

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